Picking a Needle out of a Haystack: Handwriting Biometric Identification

Two years ago, Donald Gantz, chair of the Department of Applied Information Technology in the School of Information Technology and Engineering, and Mark Walch, director of operations for The Gannon Technologies Group, began to collaborate on researching methods of biometric identification. (Biometrics involves the statistical analysis of biological observations and phenomena.)

The new technique that the two developed – handwriting derived biometric identification – can be used to analyze handwriting styles and identify their authors. It is the first successful case of using handwriting in biometric identification. “We have been able to achieve results that just two years ago were not considered possible,” says Walsh.

Handwriting derived biometric identification can be utilized in forensic document examination. Forensic document examination combines the identification of individual handwriting samples based on personal features unique to each writer with a statistical foundation that will support expert witness testimony in court cases.

“Biometric information resides in a body of features similar to the features that support character recognition,” says Gantz. “Graphs extracted from handwriting contain an abundance of information unique to the author. An author’s biometric identity is defined through the measurements that are determined to characterize that author’s writing in the sense that those measurements have the power to distinguish the author’s writing from that of other authors.”

Gannon chose to work with George Mason after carefully reviewing several programs at different institutions.

“Since our objective was to build a working tool for handwriting biometrics, we were looking for statistical guidance rooted in practical applications,” Walch explains. “We were attracted to the university because of the reputation of its statistics program and qualifications of individuals in that program. Our relationship with Dr. Gantz and his colleagues worked, and continues to work, extremely well.”

Gantz and Walch built upon isomorphic graph matching, invented by Walch to convert images of handwritten documents into electronic text, which uses graph-theory to convert handwriting into mathematical graphs. The graphs can then be analyzed for their topology and geometric features and handwriting style, such as pen strokes, loops and crossed lines, to come up with measurement data.

Donald GantzCreative Services photo

“Isomorphic graph matching showed promise for biometric identification because it is capable of recognizing the same character, or group of characters, from different writing samples,” says Walch. “These samples can be produced by the same person or several individuals. Once similar characters are recognized from different writing samples, the technology establishes the correct ‘alignment’ between corresponding features of the recognized characters.

“Given that we are able to compare aligned versions of the same character from different writing samples, we can extract numerous physical measurements upon which to perform an analysis. Even a simple character such as a lowercase letter ‘a’ can produce hundreds of measures.”

To test their technique, the researchers used a Federal Bureau of Investigation handwriting database that included more than 5,000 handwriting samples from 500 individuals.

Gantz and Walch’s new technique has been identified by the FBI, which is supporting their research, as one with the ability to make forensic document examination as scientifically reliable and accurate as fingerprint and DNA analysis. They have been invited to numerous meetings to discuss their technique, including, most recently, the American Association for the Advancement of Science’s annual meeting, which was held last month in St. Louis.